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TradingAgents/FRED_MACRO_INTEGRATION.md

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FRED API Macro Data Integration

Summary

Added FRED (Federal Reserve Economic Data) API support to the TradingAgents vendor methods system for macroeconomic analysis, including a new Macro Analyst agent.

Files Added

1. tradingagents/dataflows/macro_utils.py

New module providing FRED API integration with the following functions:

  • get_fred_api_key() - Get FRED API key from config or environment
  • get_fred_data(series_id, start_date, end_date) - Core FRED API wrapper
  • get_treasury_yield_curve(curr_date) - Treasury yield curve data with inversion analysis
  • get_economic_indicators_report(curr_date, lookback_days=90) - Comprehensive economic indicators
    • Federal Funds Rate
    • Consumer Price Index (CPI)
    • Producer Price Index (PPI)
    • Unemployment Rate
    • Nonfarm Payrolls
    • GDP Growth Rate
    • ISM Manufacturing PMI
    • Consumer Confidence
    • VIX (Market Volatility)
  • get_fed_calendar_and_minutes(curr_date) - Federal Reserve meeting calendar and policy updates
  • get_macro_economic_summary(curr_date, lookback_days=90) - Complete macro economic analysis combining all components

2. tradingagents/agents/analysts/macro_analyst.py

New macro analyst agent that uses FRED API tools to analyze economic conditions:

  • Analyzes Federal Reserve policy and economic indicators
  • Evaluates inflation, employment, and growth trends
  • Assesses Treasury yield curve and recession signals
  • Provides market implications and trading considerations

3. tradingagents/agents/utils/macro_data_tools.py

Tool wrapper functions for LangChain integration:

  • get_economic_indicators(curr_date, lookback_days) - Comprehensive economic indicators
  • get_yield_curve(curr_date) - Treasury yield curve with inversion analysis
  • get_fed_calendar(curr_date) - Fed meeting calendar and policy updates

Files Modified

4. tradingagents/dataflows/interface.py

Updated vendor routing system to include FRED macro data:

Added Imports:

from .macro_utils import get_economic_indicators_report, get_treasury_yield_curve, get_fed_calendar_and_minutes

Updated VENDOR_LIST:

VENDOR_LIST = [
    "local",
    "yfinance",
    "openai",
    "google",
    "fred"  # New
]

New TOOLS_CATEGORIES Entry:

"macro_data": {
    "description": "Macroeconomic indicators and Federal Reserve data",
    "tools": [
        "get_economic_indicators",
        "get_yield_curve",
        "get_fed_calendar"
    ]
}

New VENDOR_METHODS Entries:

# macro_data
"get_economic_indicators": {
    "fred": get_economic_indicators_report,
},
"get_yield_curve": {
    "fred": get_treasury_yield_curve,
},
"get_fed_calendar": {
    "fred": get_fed_calendar_and_minutes,
},

5. tradingagents/agents/__init__.py

Added macro analyst to exports:

from .analysts.macro_analyst import create_macro_analyst

__all__ = [
    # ... existing exports ...
    "create_macro_analyst",
]

6. tradingagents/agents/utils/agent_utils.py

Added macro tool imports:

from tradingagents.agents.utils.macro_data_tools import (
    get_economic_indicators,
    get_yield_curve,
    get_fed_calendar
)

7. tradingagents/graph/setup.py

Added macro analyst option to graph setup:

def setup_graph(
    self, selected_analysts=["market", "social", "news", "fundamentals"]
):
    """Set up and compile the agent workflow graph.

    Args:
        selected_analysts (list): List of analyst types to include. Options are:
            - "market": Market analyst
            - "social": Social media analyst
            - "news": News analyst
            - "fundamentals": Fundamentals analyst
            - "macro": Macro economic analyst  # New!
    """
    # ... existing analyst setup ...
    
    if "macro" in selected_analysts:
        analyst_nodes["macro"] = create_macro_analyst(
            self.quick_thinking_llm
        )
        delete_nodes["macro"] = create_msg_delete()
        tool_nodes["macro"] = self.tool_nodes["macro"]

8. tradingagents/graph/trading_graph.py

Added macro tools import and tool node:

from tradingagents.agents.utils.agent_utils import (
    # ... existing imports ...
    get_economic_indicators,
    get_yield_curve,
    get_fed_calendar
)

def _create_tool_nodes(self) -> Dict[str, ToolNode]:
    return {
        # ... existing tool nodes ...
        "macro": ToolNode(
            [
                get_economic_indicators,
                get_yield_curve,
                get_fed_calendar,
            ]
        ),
    }

Configuration Required

To use FRED API features, set the FRED API key via:

  1. Environment Variable:

    export FRED_API_KEY="your_api_key_here"

  2. Or via Config System: The get_fred_api_key() function will check:

    • Config system via get_api_key("fred_api_key", "FRED_API_KEY")
    • Environment variable FRED_API_KEY

  3. Get a Free API Key:

Usage Examples

Enable Macro Analyst in Graph

from tradingagents.graph.trading_graph import TradingAgentsGraph

# Create graph with macro analyst enabled
graph = TradingAgentsGraph(
    selected_analysts=["market", "fundamentals", "macro"],  # Include "macro"
    debug=True,
    config=your_config
)

# Run analysis
result = graph.propagate("AAPL", "2025-10-06")

Via Vendor Routing System

from tradingagents.dataflows.interface import route_to_vendor

# Get economic indicators
indicators = route_to_vendor(
    "get_economic_indicators",
    curr_date="2025-10-06",
    lookback_days=90
)

# Get yield curve
yield_curve = route_to_vendor(
    "get_yield_curve",
    curr_date="2025-10-06"
)

# Get Fed calendar
fed_calendar = route_to_vendor(
    "get_fed_calendar",
    curr_date="2025-10-06"
)

Direct Function Calls

from tradingagents.dataflows.macro_utils import (
    get_economic_indicators_report,
    get_treasury_yield_curve,
    get_fed_calendar_and_minutes,
    get_macro_economic_summary
)

# Complete macro analysis
summary = get_macro_economic_summary(
    curr_date="2025-10-06",
    lookback_days=90
)

# Individual components
indicators = get_economic_indicators_report("2025-10-06", 90)
yield_curve = get_treasury_yield_curve("2025-10-06")
fed_data = get_fed_calendar_and_minutes("2025-10-06")

Integration with Macro Analyst

The macro analyst can now use these tools through the vendor routing system. The tools are automatically available through the macro_data category:

# In agent configuration
config = {
    "data_vendors": {
        "macro_data": "fred"  # Use FRED for macro data
    }
}

Data Returned

All functions return formatted markdown strings suitable for LLM analysis:

  • Economic Indicators: Markdown tables with current values, changes, and analysis
  • Yield Curve: Markdown table with maturities, yields, and inversion warnings
  • Fed Calendar: FOMC meeting schedule and policy trajectory
  • Trading Implications: Actionable insights for different economic scenarios

PR Compatibility Notes

Changes were made with minimal modifications to existing code:

  1. ✅ New files only - macro_utils.py, macro_analyst.py, macro_data_tools.py are new additions
  2. ✅ Additive changes - Only added new entries to existing dictionaries and imports
  3. ✅ No breaking changes - Existing functionality unchanged
  4. ✅ Follows existing patterns - Uses same vendor routing and analyst architecture
  5. ✅ Consistent naming - Follows existing naming conventions (get_*, create_*_analyst patterns)
  6. ✅ Optional feature - Macro analyst is opt-in via selected_analysts parameter

Testing

To verify the integration works:

# Test FRED API connection
from tradingagents.dataflows.macro_utils import get_fred_data

result = get_fred_data("FEDFUNDS", "2025-01-01", "2025-10-06")
print(result)

# Test vendor routing
from tradingagents.dataflows.interface import route_to_vendor

indicators = route_to_vendor(
    "get_economic_indicators",
    curr_date="2025-10-06",
    lookback_days=30
)
print(indicators)

Dependencies

No new dependencies required. Uses existing dependencies:

  • requests - For FRED API calls
  • pandas - For data manipulation
  • datetime - For date handling
  • Existing config system for API key management

Future Enhancements

Potential improvements:

  • Add caching for FRED API responses (similar to YFinanceDataProvider)
  • Add more FRED series (housing data, commodity prices, etc.)
  • Add international economic indicators
  • Add custom FRED series ID support for advanced users